def h13cn_Tex_vs_density_A_myradex(save=True, column=1e16, print_timing=False):
"""
Generates a clone of Fig. 9 from Goldsmith+'97 for h13cn.
Parameters chosen for similarity with Goldsmith '97.
"""
start = time.time()
fig = plt.figure()
ax = fig.add_subplot(111)
density_array = np.logspace(1, 6.5, 100)
Tex_array_1_0 = np.zeros_like(density_array)
Tex_array_3_2 = np.zeros_like(density_array)
Tex_array_4_3 = np.zeros_like(density_array)
for i, density in enumerate(density_array):
od = h13cn_myradex_interface.myradex_h13cn(kinetic_temperature=20,
column_density=column,
collider_density=density)
new_T = od['table']
Tex_array_1_0[i] = new_T[0]['Tex']
Tex_array_3_2[i] = new_T[2]['Tex']
Tex_array_4_3[i] = new_T[3]['Tex']
ax.plot(np.log10(density_array), Tex_array_1_0, '-', lw=1.5, color='b')
ax.plot(np.log10(density_array), Tex_array_3_2, '--', lw=1.5, color='r')
ax.plot(np.log10(density_array), Tex_array_4_3, '-.', lw=2, color='purple')
ax.set_ylim(0, 25)
ax.set_xlim(1, 6.5)
fontdict = {'family': 'serif'}
ax.set_ylabel("EXCITATION TEMPERATURE/K", fontdict=fontdict)
ax.set_xlabel("LOG (MOLECULAR HYDROGEN DENSITY/CM$^{-3}$)",
fontdict=fontdict)
ax.text(1.5, 20, "H$^{13}$CN, T = 20 K", fontsize=18, family='serif')
ax.text(5, 22, "$J = 1 - 0$", fontsize=16, family='serif', color='b')
ax.text(3.6, 7, "$J = 4 - 3$", fontsize=16, family='serif', color='purple')
ax.text(5.6, 4, "$J = 3 - 2$", fontsize=16, family='serif', color='r')
ax.set_title("version A.myradex")
ax.minorticks_on()
if save:
fig.savefig("h13cn_Tex_vs_density_A_myradex.pdf")
plt.show()
end = time.time()
if print_timing:
print(end - start)
return fig
def h13cn_fc_vs_temperature_myradex(save=True,
print_timing=False,
n_points=20):
"""
Generates a clone of Fig. 3 from Plume+'12 for h13cn
Parameters chosen to match astrophysical hot corino.
"""
# Plume '12 claims to use an abundance of 2e-7 (i.e. one C18O for every 500 x 10^4 H2 atoms)
# but I find that 5e-7 matches the appearance much more closely.
column = 1e10
start = time.time()
# J_upper_list = [2,3,5,7,8,9,11,15]
# J_lower_list = [x-1 for x in J_upper_list]
fig = plt.figure()
ax = fig.add_subplot(111)
density_list = [1e6, 1e7, 1e8, 1e9]
temperature_array = np.linspace(10, 400, n_points)
f_c_array_n6 = np.zeros_like(temperature_array)
f_c_array_n7 = np.zeros_like(temperature_array)
f_c_array_n8 = np.zeros_like(temperature_array)
f_c_array_n9 = np.zeros_like(temperature_array)
f_c_array_list = [f_c_array_n6, f_c_array_n7, f_c_array_n8, f_c_array_n9]
for j, density in enumerate(density_list):
for i, temp in enumerate(temperature_array):
od = h13cn_myradex_interface.myradex_h13cn(
kinetic_temperature=temp,
column_density=column,
collider_density=density)
new_T = od['table']
# use the correction_factor code here!
f_c = correction_factor_given_myradex_output(
od['f_occupations'], h13cn_J_lower_list)
f_c_array_list[j][i] = f_c
ax.plot(temperature_array,
f_c_array_n6,
'g--',
lw=1.5,
label=r'$n = 10^6\ \rm{cm}^{-3}$')
ax.plot(temperature_array,
f_c_array_n7,
'b-',
lw=1.5,
label=r'$n = 10^7\ \rm{cm}^{-3}$')
ax.plot(temperature_array,
f_c_array_n8,
'r:',
lw=2,
label=r'$n = 10^8\ \rm{cm}^{-3}$')
ax.plot(temperature_array,
f_c_array_n9,
'-.',
color='purple',
lw=2,
label=r'$n = 10^9\ \rm{cm}^{-3}$')
ax.legend(frameon=False, loc='upper center', fontsize=18)
ax.set_xlim(0, 400)
# ax.set_ylim(1.6, 2)
# ax.set_xticks([0,100,200,300,400])
# ax.set_yticks([1.6,1.7,1.8,1.9,2])
fontdict = {'family': 'serif', 'fontsize': 16}
ax.set_ylabel("Correction Factor", fontdict=fontdict)
ax.set_xlabel("Temp (K)", fontdict=fontdict)
ax.minorticks_on()
if save:
ax.set_ylim(1, 4)
fig.savefig("h13cn_fc_vs_temperature_myradex.pdf")
np.savetxt("h13cn_fc_v_T_myr_temperature_array.txt", temperature_array)
np.savetxt("h13cn_fc_v_T_myr_fc_array_n6.txt", f_c_array_n6)
np.savetxt("h13cn_fc_v_T_myr_fc_array_n7.txt", f_c_array_n7)
np.savetxt("h13cn_fc_v_T_myr_fc_array_n8.txt", f_c_array_n8)
np.savetxt("h13cn_fc_v_T_myr_fc_array_n9.txt", f_c_array_n9)
plt.show()
end = time.time()
if print_timing:
print(end - start)
return fig
def h13cn_fc_vs_density_A_myradex(save=True, print_timing=False):
"""
Generates a clone of Fig. 10 from Goldsmith+'97 for h13cn
Parameters chosen for similarity with Goldsmith '97.
"""
start = time.time()
fig = plt.figure()
ax = fig.add_subplot(111)
density_array = np.logspace(1, 7, 100)
temperature_list = [10, 30, 50]
column = 1e10
f_c_array_10K = np.zeros_like(density_array)
f_c_array_30K = np.zeros_like(density_array)
f_c_array_50K = np.zeros_like(density_array)
f_c_array_list = [f_c_array_10K, f_c_array_30K, f_c_array_50K]
for j, temp in enumerate(temperature_list):
for i, rho in enumerate(density_array):
od = h13cn_myradex_interface.myradex_h13cn(
kinetic_temperature=temp,
column_density=column,
collider_density=rho)
new_T = od['table']
# use the correction_factor code here!
f_c = correction_factor_given_myradex_output(
od['f_occupations'], h13cn_J_lower_list)
f_c_array_list[j][i] = f_c
ax.plot(np.log10(density_array), f_c_array_10K, '-', lw=1.5)
ax.plot(np.log10(density_array), f_c_array_30K, ':', lw=2)
ax.plot(np.log10(density_array), f_c_array_50K, '--', lw=1.5)
ax.set_ylim(1, 3)
ax.set_xlim(2, 7.5)
fontdict = {'family': 'serif'}
ax.set_ylabel("CORRECTION FACTOR FOR COLUMN DENSITY", fontdict=fontdict)
ax.set_xlabel("LOG (MOLECULAR HYDROGEN DENSITY/CM$^{-3}$)",
fontdict=fontdict)
ax.text(3, 2, "H$^{13}$CN", fontsize=18, family='serif')
ax.text(4.5,
2.5,
r"$T_k = 10\ \rm{K}$",
fontsize=16,
family='serif',
color='b')
ax.text(4.6,
2.25,
r"$T_k = 30\ \rm{K}$",
fontsize=16,
family='serif',
color='g')
ax.text(6,
1.5,
r"$T_k = 50\ \rm{K}$",
fontsize=16,
family='serif',
color='r')
ax.text(2.5,
1.2,
r"$J_u=1,\ 3,\ 4,\ 6,\ 7,\ 8,\ 9,\ 10$ OBSERVED",
fontsize=14,
family='serif')
ax.set_title("version A.myradex")
ax.minorticks_on()
if save:
fig.savefig("h13cn_fc_vs_density_A_myradex.pdf")
plt.show()
end = time.time()
if print_timing:
print(end - start)
return fig
def h13cn_fc_vs_density_B_myradex(save=True, print_timing=False):
"""
Generates a clone of Fig. 10 from Goldsmith+'97 for h13cn
Parameters chosen for similarity with astrophysical hot corino.
"""
start = time.time()
fig = plt.figure()
ax = fig.add_subplot(111)
density_array = np.logspace(4, 8.5, 100)
temperature_list = [50, 100, 200]
column = 1e10
f_c_array_50K = np.zeros_like(density_array)
f_c_array_100K = np.zeros_like(density_array)
f_c_array_200K = np.zeros_like(density_array)
f_c_array_list = [f_c_array_50K, f_c_array_100K, f_c_array_200K]
for j, temp in enumerate(temperature_list):
for i, rho in enumerate(density_array):
od = h13cn_myradex_interface.myradex_h13cn(
kinetic_temperature=temp,
column_density=column,
collider_density=rho)
new_T = od['table']
# use the correction_factor code here!
f_c = correction_factor_given_myradex_output(
od['f_occupations'], h13cn_J_lower_list)
f_c_array_list[j][i] = f_c
ax.plot(np.log10(density_array), f_c_array_50K, 'b-', lw=1.5)
ax.plot(np.log10(density_array), f_c_array_100K, 'g:', lw=2)
ax.plot(np.log10(density_array), f_c_array_200K, 'r--', lw=1.5)
ax.set_ylim(1, 2.5)
ax.set_xlim(4, 8.5)
fontdict = {'family': 'serif'}
ax.set_ylabel("CORRECTION FACTOR FOR COLUMN DENSITY", fontdict=fontdict)
ax.set_xlabel("LOG (MOLECULAR HYDROGEN DENSITY/CM$^{-3}$)",
fontdict=fontdict)
ax.text(4.5, 2, "H$^{13}$CN", fontsize=18, family='serif')
ax.text(6.75,
1.65,
r"$T_k = 50\ \rm{K}$",
fontsize=16,
family='serif',
color='b')
ax.text(7.5,
1.3,
r"$T_k = 100\ \rm{K}$",
fontsize=16,
family='serif',
color='g')
ax.text(7.75,
1.75,
r"$T_k = 200\ \rm{K}$",
fontsize=16,
family='serif',
color='r')
string_of_J_uppers = r'\ ,'.join([str(x) for x in h13cn_J_upper_list])
ax.text(4.5,
1.2,
r"$J_u={0}$ OBSERVED".format(string_of_J_uppers),
fontsize=14,
family='serif')
ax.set_title("version B.myradex")
ax.minorticks_on()
if save:
fig.savefig("h13cn_fc_vs_density_B_myradex.pdf")
plt.show()
end = time.time()
if print_timing:
print(end - start)
return fig
print correction_factor_given_myradex_output(f_occupations, observed_lines)
# now let's do something fancier
temp_array = [10, 80, 200, 400]
fig2 = plt.figure()
ax2 = fig2.add_subplot(111)
for T in temp_array:
loop_params = params.copy()
loop_params['tkin'] = T
od = h13cn_myradex_interface.myradex_h13cn(
kinetic_temperature=T,
column_density=loop_params['ncol_x_cgs'],
collider_density=loop_params['h2_density_cgs'])
ax2.plot(od['energies'], od['f_occupations'], marker='o')
print "fcorr at T={0}:".format(T)
print correction_factor_given_myradex_output(od['f_occupations'],
observed_lines)
ax2.set_xlabel('E (K)')
ax2.set_ylabel('Occupation')
plt.show()